TY - JOUR
T1 - Empirically-based modeling of spatial sampling uncertainties associated with rainfall measurements by rain gauges
AU - Villarini, Gabriele
AU - Krajewski, Witold F.
N1 - Funding Information:
The first author was supported by NASA Headquarters under the Earth Science Fellowship Grant NNX06AF23H. The second author acknowledges partial support of the Rose and Joseph Summers endowment. The data used were supplied by the British Atmospheric Data Centre from the NERC Hydrological Radar Experiment Dataset ( http://www.badc.rl.ac.uk/data/hyrex/ ). The authors would like to acknowledge four anonymous reviewers for their helpful comments.
PY - 2008/7
Y1 - 2008/7
N2 - In the quantitative evaluation of radar-rainfall products (maps), rain gauge data are generally used as a good approximation of the true ground rainfall. However, rain gauges provide accurate measurements for a specific location, while radar estimates represent areal averages. Because these sampling discrepancies could introduce noise into the comparisons between these two sensors, they need to be accounted for. In this study, the spatial sampling error is defined as the ratio between the measurements by a single rain gauge and the true areal rainfall, defined as the value obtained by averaging the measurements by an adequate number of gauges within a pixel. Using a non-parametric scheme, the authors characterize its full statistical distribution for several spatial (4, 16 and 36 km2) and temporal (15 min and hourly) scales. To accomplish this task, a large dataset (more than six years) of rain gauge measurements obtained through a highly dense rain gauge network deployed in the Brue catchment in southwest England is used. The authors show that the standard deviation of the spatial sampling error decreases with increasing rainfall intensity and accumulation time and increases with increasing pixel size. Additionally, the authors show how the Laplace distribution could be used to model the distribution of spatial sampling errors for the spatial and temporal scales considered in this study.
AB - In the quantitative evaluation of radar-rainfall products (maps), rain gauge data are generally used as a good approximation of the true ground rainfall. However, rain gauges provide accurate measurements for a specific location, while radar estimates represent areal averages. Because these sampling discrepancies could introduce noise into the comparisons between these two sensors, they need to be accounted for. In this study, the spatial sampling error is defined as the ratio between the measurements by a single rain gauge and the true areal rainfall, defined as the value obtained by averaging the measurements by an adequate number of gauges within a pixel. Using a non-parametric scheme, the authors characterize its full statistical distribution for several spatial (4, 16 and 36 km2) and temporal (15 min and hourly) scales. To accomplish this task, a large dataset (more than six years) of rain gauge measurements obtained through a highly dense rain gauge network deployed in the Brue catchment in southwest England is used. The authors show that the standard deviation of the spatial sampling error decreases with increasing rainfall intensity and accumulation time and increases with increasing pixel size. Additionally, the authors show how the Laplace distribution could be used to model the distribution of spatial sampling errors for the spatial and temporal scales considered in this study.
KW - Modeling of uncertainties
KW - Rainfall
KW - Sampling error
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U2 - 10.1016/j.advwatres.2008.04.007
DO - 10.1016/j.advwatres.2008.04.007
M3 - Article
AN - SCOPUS:44649087596
SN - 0309-1708
VL - 31
SP - 1015
EP - 1023
JO - Advances in Water Resources
JF - Advances in Water Resources
IS - 7
ER -